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In the context of statistical learning, the Information Bottleneck method seeks a right balance between accuracy and generalization capability through a suitable tradeoff between compression complexity, measured by minimum description…

Information Theory · Computer Science 2021-02-16 Mohammad Mahdi Mahvari , Mari Kobayashi , Abdellatif Zaidi

Consider a receiver in a multi-user network that wishes to decode several messages. Simultaneous joint typicality decoding is one of the most powerful techniques for determining the fundamental limits at which reliable decoding is possible.…

Information Theory · Computer Science 2019-01-11 Sung Hoon Lim , Chen Feng , Adriano Pastore , Bobak Nazer , Michael Gastpar

This paper addresses the problem of coding a continuous random source correlated with another source which is only available at the decoder. The proposed approach is based on the extension of the channel coding concept of syndrome from the…

Information Theory · Computer Science 2007-10-11 Lorenzo Cappellari

We consider the problem of encoding two-dimensional arrays, whose elements come from a total order, for answering \topk{} queries. The aim is to obtain encodings that use space close to the information-theoretic lower bound, which can be…

Data Structures and Algorithms · Computer Science 2021-07-13 Seungbum Jo , Srinivasa Rao Satti

We are interested in how to best communicate a (usually real valued) source to a number of destinations (sinks) over a network with capacity constraints in a collective fidelity metric over all the sinks, a problem which we call joint…

Information Theory · Computer Science 2007-07-13 Nima Sarshar , Xiaolin Wu

Algebraic space-time coding allows for reliable data exchange across fading multiple-input multiple-output channels. A powerful technique for decoding space-time codes in Maximum-Likelihood (ML) decoding, but well-performing and widely-used…

Information Theory · Computer Science 2015-01-28 Amaro Barreal , Camilla Hollanti , David Karpuk

A novel class of achievable rate regions is obtained for the K-receiver broadcast channel with two groupcast messages. The associated achievability schemes are parameterized by an expansion of the message set which then determines how…

Information Theory · Computer Science 2020-01-28 Mohamed Salman , Mahesh K. Varanasi

Medical image segmentation is a fundamental yet challenging task due to the arduous process of acquiring large volumes of high-quality labeled data from experts. Contrastive learning offers a promising but still problematic solution to this…

Computer Vision and Pattern Recognition · Computer Science 2025-02-14 Shuang Zeng , Lei Zhu , Xinliang Zhang , Micky C Nnamdi , Wenqi Shi , J Ben Tamo , Qian Chen , Hangzhou He , Lujia Jin , Zifeng Tian , Qiushi Ren , Zhaoheng Xie , Yanye Lu

This paper investigates the decoding of certain Gabidulin codes that were transmitted over a channel with space-symmetric errors. Space-symmetric errors are additive error matrices that have the property that their column and row spaces are…

Information Theory · Computer Science 2021-02-05 Thomas Jerkovits , Vladimir Sidorenko , Antonia Wachter-Zeh

We propose an easy-to-implement hard-decision majority-logic decoding algorithm for Reed-Muller codes RM(r,m) with m >= 3, m/2 >= r >= 1. The presented algorithm outperforms the best known majority-logic decoding algorithms and offers…

Information Theory · Computer Science 2018-07-03 Juliane Bertram , Peter Hauck , Michael Huber

We present a new information-theoretic definition and associated results, based on list decoding in a source coding setting. We begin by presenting list-source codes, which naturally map a key length (entropy) to list size. We then show…

Information Theory · Computer Science 2012-10-09 Flavio du Pin Calmon , Muriel Médard , Linda M. Zeger , João Barros , Mark M. Christiansen , Ken. R. Duffy

Undersampled inverse problems occur everywhere in the sciences including medical imaging, radar, astronomy etc., yielding underdetermined linear or non-linear reconstruction problems. There are now a myriad of techniques to design decoders…

Optimization and Control · Mathematics 2023-11-29 Nina Maria Gottschling , Paolo Campodonico , Vegard Antun , Anders C. Hansen

Symmetrical Multilevel Diversity Coding (SMDC) is a network compression problem introduced by Roche (1992) and Yeung (1995). In this setting, a simple separate coding strategy known as superposition coding was shown to be optimal in terms…

Information Theory · Computer Science 2016-11-18 Anantharaman Balasubramanian , Hung D. Ly , Shuo Li , Tie Liu , Scott L. Miller

We consider a problem of coding for computing, where the decoder wishes to estimate a function of its local message and the source message at the encoder within a given distortion. We show that the rate-distortion function can be…

Information Theory · Computer Science 2022-05-18 Deheng Yuan , Tao Guo , Bo Bai , Wei Han

We study the maximum $k$-colorable subgraph (M$k$CS) problem, which consists in finding a largest $k$-colorable induced subgraph in a given graph. We consider a Semidefinite Programming (SDP) relaxation for the M$k$CS problem and regard its…

Optimization and Control · Mathematics 2026-05-05 Mathijs Barkel , Renata Sotirov

In social network analysis, the size of the k-core, i.e., the maximal induced subgraph of the network with minimum degree at least k, is frequently adopted as a typical metric to evaluate the cohesiveness of a community. We address the…

Optimization and Control · Mathematics 2023-05-03 Martina Cerulli , Domenico Serra , Carmine Sorgente , Claudia Archetti , Ivana Ljubic

Multi-label classification (MLC) refers to the problem of tagging a given instance with a set of relevant labels. Most existing MLC methods are based on the assumption that the correlation of two labels in each label pair is symmetric,…

Machine Learning · Computer Science 2024-10-04 Xingyu Zhao , Yuexuan An , Lei Qi , Xin Geng

The problem of error-control in random linear network coding is considered. A ``noncoherent'' or ``channel oblivious'' model is assumed where neither transmitter nor receiver is assumed to have knowledge of the channel transfer…

Information Theory · Computer Science 2008-03-25 Ralf Koetter , Frank Kschischang

The problem of error control in random linear network coding is addressed from a matrix perspective that is closely related to the subspace perspective of K\"otter and Kschischang. A large class of constant-dimension subspace codes is…

Information Theory · Computer Science 2019-05-07 Danilo Silva , Frank R. Kschischang , Ralf Kötter

Interleaved Reed-Solomon codes admit efficient decoding algorithms which correct burst errors far beyond half the minimum distance in the random errors regime, e.g., by computing a common solution to the Key Equation for each Reed-Solomon…

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